agentsclimarketplace

Write a goal

Skill hamza-ali-shahjahan/hamzaish/factory/skills/write-a-goal

Turn a rough ambition into a measurable, REACHABLE goal — a capability statement, a precisely-named metric, ≥2 numeric evals, an acceptance rule, and non-goals — with a feasibility check that catches impossible or game-able targets before you chase them. Pair with /goal (which pursues a goal autonomously).From its SKILL.md

Install
npx -y skills add hamza-ali-shahjahan/hamzaish --skill write-a-goal

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

4.9 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

/write-a-goal

Usage: /write-a-goal <the ambition, or what "good" looks like>

A goal you can't measure is a wish. A goal you can't reach is a trap. A goal a degenerate output can fake is a lie. This skill turns an ambition into a goal that /goal can autonomously pursue and a fresh-eyes agent can actually certify — and it refuses to hand you a target that's impossible or game-able.

The shape a good goal must clear

  1. Capability statement — one sentence: "Given X, the system does Y." Concrete, observable.
  2. The exact metric — the single thing measured, named precisely enough that two people would compute the same number (see Check A).
  3. ≥2 numeric evals — real test cases, each with a target number and how it's scored. One eval is an anecdote; two+ is a bar.
  4. Acceptance rule — when is it done? (e.g. "every eval ≥ target on a fresh run, confirmed by a fresh-eyes agent.")
  5. Non-goals — what this explicitly is not, so the loop doesn't gold-plate the wrong thing.

The two checks that make or break it (hard-won)

Check A — Pin the exact metric (kill vague percentages)

"Make it 99% similar" is meaningless until you answer similar HOW. The same artifact can score 20% or 95% depending on the measure. Force the choice:

  • Name the measure (e.g. visual SSIM on edge maps, not "looks the same"; structural token overlap, not "matches the design"; p95 latency, not "fast").
  • State how it's computed and what tool reports it.
  • If one number hides several things, split it (e.g. "fidelity" → visual + structural + copy).
  • Robustness clause: require the metric to resist gaming. Ask "what's the dumbest output that could score high?" — if a blank/empty/degenerate result can fake the target, the metric is broken; add a guard before you trust it.

Check B — Feasibility / ceiling check (don't set a trap)

Before committing the target, pressure-test it against what the architecture can actually reach:

  • What's the theoretical ceiling for this approach? (e.g. a small local model reconstructing from a text description can't pixel-match a real site — the inputs it's missing cap it far below 100%.)
  • Is the target inside that ceiling, with headroom? If not, say so plainly and propose a reachable target instead — never accept an impossible number silently.
  • Name the lever that would raise the ceiling (a different input, a different model class) vs. the levers that just optimize within it — so effort goes where it pays.

What you do as the assistant when this is invoked

  1. Extract the ambition — what does the user actually want, and what would make them say "yes, that's it"? Ask at most one clarifying question if it's truly ambiguous.
  2. Draft the 5-part goal (capability · metric · ≥2 evals · acceptance · non-goals).
  3. Run Check A — pin the exact metric; split vague numbers; add the robustness guard.
  4. Run Check B — feasibility. If the target is unreachable or game-able, lead with that, and offer a reachable, robust alternative target (recommended-first).
  5. Output the goal spec as a small artifact (capability, metric+tool, evals with numbers, acceptance, non-goals, and the feasibility verdict).
  6. Offer to hand off to /goal to pursue it autonomously, or /full-cycle if it's a build.

Anti-patterns — real cases this skill exists to prevent

  • Vague + impossible: "Replicate this homepage to 99%." Two failures at once — the metric is undefined (visual? structural? pixel?), and the target is unreachable for the architecture (a local 14B reconstructing from a text digest plateaus ~30% visual; placeholder-vs-real images alone cap it). The fix: define the measure (visual SSIM with a blank-guard), and set a reachable bar (e.g. structural ≥ 85% + visual ≥ 70% with real images), naming "a vision model" as the lever that would raise the ceiling.
  • Game-able metric: a blank page scoring 98% because it matched the site's dark background. A target with no robustness guard rewards the dumbest output.
  • Single anecdote as a bar: one passing example ≠ a goal. Require ≥2 evals.
  • A vibe with no number: "make it feel premium." Either find a measurable proxy or admit it's a taste call, not a goal.

Companion: meta/learning-loop-rubric.md (scoring what to promote) and meta/always-recommend.md (lead with the recommendation — including when proposing a reachable target). /goal pursues a goal; /write-a-goal forges one worth pursuing.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,758. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.